单模态的表示学习负责将信息表示为计算机可以处理的数值向量或者进一步抽象为更高层的特征向量,而多模态表示学习是指通过利用多模态之间的互补性,剔除模态间的冗余性,从而学习到更好的特征表示。主要包括两大研究方向:联合表示(Joint Representations)和协同表示(Coordinated Representations)。 联合表示将多个模态的信息一起...
优势：高效且能较早融合轨迹和地图信息，如 LaneRCNN: Distributed Representations for Graph-Centric Mot...
称为“k-disks”，用于标记轨迹数据，使得可以使用小词汇量对Waymo Open Dataset进行标记，以及一个基于T...
representation and the input data. Different from general IB, our MIB regularizes both the multimodal and unimodal representations, which is a comprehensive and flexible framework that is compatible with any fusion methods. We develop three MIB variants, namely, early-fusion MIB, late-fusion MIB,...
Visual unimodal representations(CNN 和视觉表示) Language unimodal representations(语言表示) Multimodal representation learning(多模态表示) Coordinated representations(协调表示) Multimodal alignment(多模式对齐) Alignment and representation(对齐和表示) Alignment and translation(对齐和平移 (映射)) ...
Coordinated representations(协调表示):单独处理单信号,但对其施加一定的相似约束,使其成为我们所说的协调空间;适合于在测试时只有一种模式存在的应用,eg:多模式检索和转换、基础和零镜头学习, 表征技术一览表,其中[#]是综述中引用的论文编号 回到顶部 1.2、翻译: ...
Forceville, C. 2008. Metaphors in Pictures and Multimodal Representations \[M\]. Cambridge: Cambridge University Press. Forceville, C. 2016. Visual and multimodal metaphor in film: Charting the field [C] // K. Fahlenbrach...
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” in Advances in neural information processing sys- tems, 2013, pp. 3111–3119. O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, ...
The heterogeneity of multimodal data makes it challenging to construct such representations. For example, language is often symbolic while audio and visual modalities will be represented as signals. 表示:第一个基本挑战是学习如何以一种利用多种模态的互补性和冗余性的方式表示和汇总多模式数据。多模数据的...